基于卡车-无人机协同配送的双目标应急物资运送优化  

Optimizing Bi-Objective Emergency Supply Transportation Based on Synchronized Truck-Drone Delivery

作　　者：张林静 丁溢 ZHANG Linjing;DING Yi(School of Economic and Management,Southeast University,Nanjing 211189,China)

机构地区：[1]东南大学经济管理学院,南京211189

出　　处：《系统管理学报》2025年第1期81-95,共15页Journal of Systems & Management

基　　金：国家自然科学基金资助项目(72171046,71801043);国家自然科学基金重大项目(72091213);中央高校基础科研业务费资助项目(2242023K40016,2242019S20021)。

摘　　要：鉴于灾害的严重破坏性,社会各界对突发灾害的关注程度逐渐提高,研究高效合理的应急物资运送路径成为应急管理领域的紧迫任务。基于此,将卡车-无人机协同配送模式运用到灾后应急物资运送过程中,以期快速为灾民提供关键物资。首先,通过引入剥夺成本来衡量灾民因缺乏物资而感知的痛苦,进而以卡车-无人机协同配送总物流成本最小和灾民承受的剥夺成本最小为目标构建非线性整数规划模型;其次,采用改进的带精英策略的非支配排序遗传算法(INSGA-Ⅱ)对模型进行求解;最后,通过数值分析和算法比较对所提出模型及算法进行验证。结果表明:卡车-无人机协同配送模式能够有效降低物流成本和灾民痛苦;INSGA-II算法比NSGA-Ⅱ算法效果更优。Due to the severe destructiveness of natural disaster,societal attention to emergency events has been steadily increasing.Studying efficient and rational delivery routes has become an urgent task in emergency management.To address this issue,this paper proposes using a synchronized truck-drone delivery mode to transport emergency supplies during post-disaster relief efforts,aiming to rapidly deliver critical resources to affected populations.First,it introduces a deprivation cost to evaluate the suffering experienced by victims due to lack of resources and develops a synchronized truck-drone delivery routing model which is non-linear integer programming,with the goal of minimizing both the total logistics cost and the deprivation cost experienced by the disaster victims.Next,it solves the model by employing an improved elitist nondominated sorting genetic algorithm(INSGA-II).Finally,it verifies the proposed model and algorithm through numerical analysis and comparisons with other algorithms.The results indicate that the synchronized truck-drone delivery mode significantly reduces both the total logistics cost and the hardships faced by disaster victims.INSGA-II outperforms the NSGA-II algorithm in terms of effectiveness.

关 键 词：应急物资运送 卡车-无人机协同配送 灾民痛苦 双目标优化 INSGA-Ⅱ算法 

分 类 号：C93[经济管理—管理学]